• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1147-1156
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• 2010

This paper proposes a replacement policy following the expiration of a non-renewing free replacement-repair Warranty(NFFRW). The non-renewing free replacement-repair warranty is defined and then the maintenance model following the expiration of the NFRRW is studied from the user's point of view. As the criteria to determine the optimality of the maintenance policy, we consider the expected cost rate per unit time from the user's perspective. All maintenance costs of the system incurred after the expiration of the warranty are paid by the user. Given the cost structures during the life cycle of the system, we determine the optimal maintenance period following the expiration of a NFRRW. Finally, the numerical examples are presented for illustrative purposes.

• Journal of Applied Reliability
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• v.13 no.2
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• pp.77-86
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• 2013

Recently, an extended warranty of a system following the expiration of the basic warranty is becoming increasingly popular to the user. In this respect, we suggest a replacement model following the expiration of extended warranty with minimal repair warranty from the user's point of view in this paper. Under extended warranty, the failed system is minimally repaired by the manufacturer at no cost to the user during the original extended warranty period. As a criterion of the optimality, we utilize the expected cost rate per unit time during the life cycle from the user's perspective and suggest the optimal replacement period after extended warranty. Finally, a few numerical examples are given for illustrative purpose.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.98-107
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• 2008

The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unittime. This study considers a linear connected-(r, s)-ouI-of-(m, n):f lattice system whose components are orderedlike the elements of a linear (m, n)-matrix. We assume that all components are in the state 1 (operating) or 0(failed) and identical and s-independent. The system fails whenever at least one connected (r, s)-submatrix offailed components occurs. To find the optimal threshold of maintenance intervention, we use a simulatedannealing(SA) algorithm for the cost optimization procedure. The expected cost per unit time is obtained byMonte Carlo simulation. We also has made sensitivity analysis to the different cost parameters. In this study,utility maintenance model is constructed so that minimize the expense under full equipment policy throughcomparison for the full equipment policy and preventive maintenance policy. The full equipment cycle and unitcost rate are acquired by simulated annealing algorithm. The SA algorithm is appeared to converge fast inmulti-component system that is suitable to optimization decision problem.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.651-662
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• 1996

This paper concerns with preventive replacement under periodic inspections for an item (system) which is in a state of preparedness. The item is subject to wear. The item fails randomly but the failure rate depends on the accumulated wear. The item is preventively replaced if it survives a certain wear limit at periodic inspections. The foiled item is, however, replaced at periodic inspections. Given the costs for replacements and inspections, and the penalty cost of the time elapsed between failure und its detection, the optimal wear limit according to the long-run expected cost per unit time criterion is derived. It has been proved that the optimal wear limit is unique if an item has increasing weer-dependent failure rate. A numerical example for a stationary gamma wear process with Weibull distributed failure is given to show its applicability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.154-168
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• 2021

COVID-19 has been spreading all around the world, and threatening global health. In this situation, identifying and isolating infected individuals rapidly has been one of the most important measures to contain the epidemic. However, the standard diagnosis procedure with RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) is costly and time-consuming. For this reason, pooled testing for COVID-19 has been proposed from the early stage of the COVID-19 pandemic to reduce the cost and time of identifying the COVID-19 infection. For pooled testing, how many samples are tested in group is the most significant factor to the performance of the test system. When the arrivals of test requirements and the test time are stochastic, batch-service queueing models have been utilized for the analysis of pooled-testing systems. However, most of them do not consider the false-negative test results of pooled testing in their performance analysis. For the COVID-19 RT-PCR test, there is a small but certain possibility of false-negative test results, and the group-test size affects not only the time and cost of pooled testing, but also the false-negative rate of pooled testing, which is a significant concern to public health authorities. In this study, we analyze the performance of COVID-19 pooled-testing systems with false-negative test results. To do this, we first formulate the COVID-19 pooled-testing systems with false negatives as a batch-service queuing model, and then obtain the performance measures such as the expected number of test requirements in the system, the expected number of RP-PCR tests for a test sample, the false-negative group-test rate, and the total cost per unit time, using the queueing analysis. We also present a numerical example to demonstrate the applicability of our analysis, and draw a couple of implications for COVID-19 pooled testing.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.107-117
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• 2002

In this paper we present the optimal replacement policies following the expiration of combination warranty. We consider two types of combination warranty policies: renewing warranty and non-renewing warranty. The criterion used to determine the optimal replacement period is the expected cost rate per unit time from the user'perspective. The optimal maintenance period following the expiration of combination warranty is obtained. Some numerical examples are presented for illustrative purpose.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.55-65
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• 2002

In this paper we present a Bayesian approach for determining an optimal maintenance policy following the expiration of warranty for a repairable system. We consider two types of warranty policies : non-renewing free replacement warranty (NFRW) and non-renewing pro-rata warranty (NPRW). The mathematical formula of the expected cost rate per unit time is obtained for NFRW and NPRW, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. We illustrate the use of our approach with simulated data.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.21-31
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• 2002

This paper considers a Bayesian approach to determine an optimal replacement policy for a repairable system with warranty period. The mathematical formula of the expected cost rate per unit time is obtained for two cases : RFRW(renewing free-replacement warranty) and RPRW(renewing pro-rata warranty). When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal replacement policy. Some numerical examples are presented for illustrative purpose.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.4
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• pp.47-55
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• 2009

This paper estimates interruption cost assessment for industrial load. For executing In this way first, we research customer interruption cost(CIC) for industrial load about 1,026 unit. And to assess industrial load in D/L calculate sector customer damage function(SCDF) using CIC. Second, we compute distribution reliability through annual failure rate, repair time and so on, and then, Third, distribution system that calculate VBDRA for industrial load per alternative assesses interruption cost.

• Journal of Korean Society for Quality Management
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• v.43 no.4
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• pp.471-488
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• 2015

Purpose: Double sampling $T^2$ chart is a useful tool for detecting a relatively small shift in process mean when the process is controlled by multiple variables. This paper finds the optimal design of the double sampling $T^2$ chart in both economical and statistical sense under Weibull failure model. Methods: The expected cost function is mathematically derived using recursive equation approach. The optimal designs are found using a genetic algorithm for numerical examples and compared to those of single sampling $T^2$ chart. Sensitivity analysis is performed to see the parameter effects. Results: The proposed design outperforms the optimal design of the single sampling $T^2$ chart in terms of the expected cost per unit time and Type-I error rate for all the numerical examples considered. Conclusion: Double sampling $T^2$ chart can be designed to satisfy both economic and statistical requirements under Weibull failure model and the resulting design is better than the single sampling counterpart.